Currently businesses are not reporting environmental information in a clear, consistent,
comparable and transparent manner "en masse". Supplementary government data are not
available and current estimation methods do not enable efficient generation of
environmental data (emissions and water use data) for many or all businesses in a given
area. Without such estimates or methods for estimation, it is difficult to identify or
attribute environmental impacts to individual business and encourage businesses to
acknowledge and reduce these impacts. Generation of such emissions and water use
estimates for groups of businesses can also have wider uses such as in the assessment of the
technical and economic feasibility of waste management schemes. To be conducted
effectively, this requires detailed and disaggregated estimates of relevant wastes for all
businesses in an area.
To deal with these problems and gaps, this study generates a new framework model capable
of estimating the direct and indirect GHG emissions, C&I waste, food waste and water use
for individual businesses of a specific sector, or all businesses of a specific sector within a
defined area. A chapter is devoted to formal documentation of the framework and data; a
second presents methods for testing the framework. To illustrate the framework, the PhD
presents a case study for hospitality and food retail businesses in Southampton using best
estimates. Key to the development of the model is to assess the reliability of estimates.
Three chapters are devoted to this. This allows an indication of reliability and robustness of
the estimates of this PhD. Best estimates for GHGs applied a new approach that resulted in
a 126 sector model which is unique to this UK study. The final chapter identifies key
findings and added value of the work and draws conclusions for the dissertation.